1
|
Yu H, Hu W, Lin C, Xu L, Liu H, Luo L, Chen R, Huang J, Chen W, Yang C, Kong D, Ding Y. Polymorphisms analysis for association between ADIPO signaling pathway and genetic susceptibility to T2DM in Chinese han population. Adipocyte 2021; 10:463-474. [PMID: 34641739 PMCID: PMC8525967 DOI: 10.1080/21623945.2021.1978728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The aim of the present study is to explored the relationship between ADIPO signalling pathway and T2DM, to provide clues for further study of the pathogenesis of T2DM and to determine the possible drug targets. This study employed a case-control study design. Twenty-three single nucleotide polymorphisms (SNPs) of 13 genes in the selected ADIPO signalling pathway were genotyped by SNPscanTM kit. All statistical analysis was performed by SPSS 25.0, PLINK 1.07, R 2.14.2, Haploview 4.2, SNPstats, and other statistical software packages. In the association analysis based on a single SNPs, rs1044471 had statistical significance in the overdominant model without adjusting covariates. Rs1042531 had statistical significance in the overdominant model. Rs12718444 had statistical significance in the recessive model. There was a linkage disequilibrium between the loci within 9 genes, and the two loci in RXRA gene did not form blocks. Four kernel functions were used for SNPs set analysis based on ADIPO signalling pathway showed that there was no statistical significance whether covariates were added or not, P>0.05.According to our research results, it is found that some single nucleotide polymorphisms (ADIPOR2 rs1044471, PCK1 rs1042531, GLUT1 rs12718444) in the adiponectin signalling pathway may be associated with T2DM
Collapse
Affiliation(s)
- Haibing Yu
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Institute of Nephrology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Wei Hu
- Shenzhen Center for Chronic Disease Control, Shenzhen, Guangdong, China
| | - Chunwen Lin
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Lin Xu
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Hao Liu
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Ling Luo
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Rong Chen
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Jialu Huang
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Weiying Chen
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Chen Yang
- Key Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Institute of Nephrology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Danli Kong
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| | - Yuanlin Ding
- Department of Epidemiology and Medical Statistics, School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China
| |
Collapse
|
2
|
Mishra SK, Dubey PK, Dhiman A, Dubey S, Verma D, Kaushik AC, Singh R, Niranjan SK, Vohra V, Mehrara KL, Kataria RS. Sequence-based structural analysis and evaluation of polymorphism in buffalo Nod-like receptor-1 gene. 3 Biotech 2019; 9:26. [PMID: 30622864 DOI: 10.1007/s13205-018-1534-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 12/14/2018] [Indexed: 12/13/2022] Open
Abstract
In this study, we have sequence characterized and analyzed the polymorphism in buffalo NOD1 (nucleotide-binding oligomerization domain 1) gene as well as its expression analysis. Full-length sequence analysis of NOD1 revealed this gene in buffalo being conserved with respect to the domain structures, similar to other species. Alternate splice variants having exon3 skipping also identified for the first time in the gene expressed in buffalo-purified peripheral blood mononuclear cells (PBMCs). Phylogenetically ruminant species were found to be clustering together and buffalo displaying maximum similarity with cattle. Sequencing of NOD1 across 12 Indian buffalo breeds identified 23 polymorphic sites within coding region, among which 16 were synonymous and 7 changes found to be non-synonymous. Four SNPs (single nucleotide polymorphisms) of them were genotyped in 393 animals belonging to 12 riverine, swamp and hybrid (riverine × swamp) buffalo populations of diverse phenotypes and utilities, showing variable allelic frequencies. Principal component analysis revealed, riverine and swamp buffaloes being distinctly placed with the distribution of breeds within the group based on the geographical isolation. Further, quantitative real-time PCR detected NOD1 expression in multiple tissues with PBMCs and lungs showing highest expression among the tissues examined. Structural analysis based on the translated amino acid sequence of buffalo NOD1 identified four protein interaction motifs LxxLL important for ligand binding. Molecular interaction analysis of iE-DAP and NOD1-LRR and their complex stability and binding-free energy studies indicated variable binding energies in buffalo and cattle NOD1. Overall, the study reveals unique structural features in buffalo NOD1, important for species-specific ligand interaction.
Collapse
|
3
|
Abo-Ismail MK, Lansink N, Akanno E, Karisa BK, Crowley JJ, Moore SS, Bork E, Stothard P, Basarab JA, Plastow GS. Development and validation of a small SNP panel for feed efficiency in beef cattle. J Anim Sci 2018; 96:375-397. [PMID: 29390120 DOI: 10.1093/jas/sky020] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 01/17/2018] [Indexed: 12/11/2022] Open
Abstract
The objective of this study was to develop and validate a customized cost-effective single nucleotide polymorphism (SNP) panel for genetic improvement of feed efficiency in beef cattle. The SNPs identified in previous association studies and through extensive analysis of candidate genomic regions and genes, were screened for their functional impact and allele frequency in Angus and Hereford breeds used as validation candidates for the panel. Association analyses were performed on genotypes of 159 SNPs from new samples of Angus (n = 160), Hereford (n = 329), and Angus-Hereford crossbred (n = 382) cattle using allele substitution and genotypic models in ASReml. Genomic heritabilities were estimated for feed efficiency traits using the full set of SNPs, SNPs associated with at least one of the traits (at P ≤ 0.05 and P < 0.10), as well as the Illumina bovine 50K representing a widely used commercial genotyping panel. A total of 63 SNPs within 43 genes showed association (P ≤ 0.05) with at least one trait. The minor alleles of SNPs located in the GHR and CAST genes were associated with decreasing effects on residual feed intake (RFI) and/or RFI adjusted for backfat (RFIf), whereas minor alleles of SNPs within MKI67 gene were associated with increasing effects on RFI and RFIf. Additionally, the minor allele of rs137400016 SNP within CNTFR was associated with increasing average daily gain (ADG). The SNPs genotypes within UMPS, SMARCAL, CCSER1, and LMCD1 genes showed significant over-dominance effects whereas other SNPs located in SMARCAL1, ANXA2, CACNA1G, and PHYHIPL genes showed additive effects on RFI and RFIf. Gene enrichment analysis indicated that gland development, as well as ion and cation transport are important physiological mechanisms contributing to variation in feed efficiency traits. The study revealed the effect of the Jak-STAT signaling pathway on feed efficiency through the CNTFR, OSMR, and GHR genes. Genomic heritability using the 63 significant (P ≤ 0.05) SNPs was 0.09, 0.09, 0.13, 0.05, 0.05, and 0.07 for ADG, dry matter intake, midpoint metabolic weight, RFI, RFIf, and backfat, respectively. These SNPs contributed to genetic variation in the studied traits and thus can potentially be used or tested to generate cost-effective molecular breeding values for feed efficiency in beef cattle.
Collapse
Affiliation(s)
- M K Abo-Ismail
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
- Animal and Poultry Production Department, Damanhour University, Damanhour, Egypt
| | - N Lansink
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
| | - E Akanno
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
| | - B K Karisa
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
| | - J J Crowley
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
- Canadian Beef Breeds Council, Calgary, AB, Canada
| | - S S Moore
- Centre for Animal Science, University of Queensland, St Lucia, Australia
| | - E Bork
- Rangeland Research Institute, Agriculture/Forestry Center, University of Alberta, Edmonton, AB, Canada
| | - P Stothard
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
| | - J A Basarab
- Alberta Agriculture and Forestry, Lacombe Research Centre, Lacombe, AB, Canada
| | - G S Plastow
- Livestock Gentec at University of Alberta, Edmonton, AB, Canada
| |
Collapse
|
4
|
Liu T, Liu M, Shang P, Jin X, Liu W, Zhang Y, Li X, Ding Y, Li Y, Wen A. Investigation into the underlying molecular mechanisms of hypertensive nephrosclerosis using bioinformatics analyses. Mol Med Rep 2018; 17:4440-4448. [PMID: 29328390 PMCID: PMC5802219 DOI: 10.3892/mmr.2018.8405] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Accepted: 11/24/2017] [Indexed: 12/11/2022] Open
Abstract
Hypertensive nephrosclerosis (HNS) is a major risk factor for end-stage renal disease. However, the underlying pathogenesis of HNS remains to be fully determined. The gene expression profile of GSE20602, which consists of 14 glomeruli samples from patients with HNS and 4 normal glomeruli control samples, was obtained from the Gene Expression Omnibus database. Gene ontology (GO) and pathway enrichment analyses were performed in order to investigate the functions and pathways of differentially expressed genes (DEGs). Pathway relation and co‑expression networks were constructed in order to identify key genes and signaling pathways involved in HNS. In total, 483 DEGs were identified to be associated with HNS, including 302 upregulated genes and 181 downregulated genes. Furthermore, GO analysis revealed that DEGs were significantly enriched in the small molecule metabolic process. In addition, pathway analysis also revealed that DEGs were predominantly involved in metabolic pathways. The tricarboxylic acid (TCA) cycle was identified as the hub pathway in the pathway relation network, whereas the sorbitol dehydrogenase (SORD) and cubulin (CUBN) genes were revealed to be the hub genes in the co‑expression network. The present study revealed that the SORD, CUBN and albumin genes as well as the TCA cycle and metabolic pathways are involved in the pathogenesis of HNS. The results of the present study may contribute to the determination of the molecular mechanisms underlying HNS, and provide insight into the exploration of novel targets for the diagnosis and treatment of HNS.
Collapse
Affiliation(s)
- Tianlong Liu
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Minna Liu
- Department of Nephrology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Peijin Shang
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Xin Jin
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Wenxing Liu
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Yikai Zhang
- Department of Pharmacy, General Hospital of Shenyang Military Region, Shenyang, Liaoning 110016, P.R. China
| | - Xinfang Li
- Department of Inorganic Chemistry, School of Pharmacy, Second Military Medical University, Shanghai 200433, P.R. China
| | - Yi Ding
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Yuwen Li
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| | - Aidong Wen
- Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, P.R. China
| |
Collapse
|
5
|
Huang J, Guo F, Zhang Z, Zhang Y, Wang X, Ju Z, Yang C, Wang C, Hou M, Zhong J. PCK1
is negatively regulated by bta-miR-26a, and a single-nucleotide polymorphism in the 3′ untranslated region is involved in semen quality and longevity of Holstein bulls. Mol Reprod Dev 2016; 83:217-25. [DOI: 10.1002/mrd.22613] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2015] [Accepted: 12/29/2015] [Indexed: 11/10/2022]
Affiliation(s)
- Jinming Huang
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Fang Guo
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Zebin Zhang
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Yuanpei Zhang
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Xiuge Wang
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Zhihua Ju
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Chunhong Yang
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Changfa Wang
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Minghai Hou
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| | - Jifeng Zhong
- Dairy Cattle Research Center; Shandong Academy of Agricultural Sciences; Shandong China
| |
Collapse
|